inverse reinforcement learning

RAPID: Robust and Agile Planner Using Inverse Reinforcement Learning for Vision-Based Drone Navigation RSS 2025 Robust Inverse Reinforcement Learning Control with Unknown States L4DC 2025 Understanding Constraint Inference in Safety-Critical Inverse Reinforcement Learning ICLR 2025 Understanding Inverse Reinforcement Learning under Overparameterization: Non-Asymptotic Analysis and Global Optimality AISTATS 2025 Adaptive Language-Guided Abstraction from Contrastive Explanations CoRL 2024 Data Poisoning to Fake a Nash Equilibria for Markov Games AAAI 2024 Decoupling regularization from the action space ICLR 2024 EMOTE: An Explainable Architecture for Modelling the Other through Empathy IJCAI 2024 Enhancing Robustness of Graph Neural Networks on Social Media with Explainable Inverse Reinforcement Learning NeurIPS 2024 Environment Design for Inverse Reinforcement Learning ICML 2024 EscIRL: Evolving Self-Contrastive IRL for Trajectory Prediction in Autonomous Driving CoRL 2024 Expectation Alignment: Handling Reward Misspecification in the Presence of Expectation Mismatch NeurIPS 2024 Getting More Juice Out of the SFT Data: Reward Learning from Human Demonstration Improves SFT for LLM Alignment NeurIPS 2024 How does Inverse RL Scale to Large State Spaces? A Provably Efficient Approach NeurIPS 2024 Hybrid Inverse Reinforcement Learning ICML 2024 Imitating Language via Scalable Inverse Reinforcement Learning NeurIPS 2024 Imitation Learning from Observation with Automatic Discount Scheduling ICLR 2024 In-Trajectory Inverse Reinforcement Learning: Learn Incrementally Before an Ongoing Trajectory Terminates NeurIPS 2024 Inverse Factorized Soft Q-Learning for Cooperative Multi-agent Imitation Learning NeurIPS 2024 Is Inverse Reinforcement Learning Harder than Standard Reinforcement Learning? A Theoretical Perspective ICML 2024 Learning Safety Constraints from Demonstrations with Unknown Rewards AISTATS 2024 Learning to Assist Humans without Inferring Rewards NeurIPS 2024 Learning Transparent Reward Models via Unsupervised Feature Selection CoRL 2024 Learning true objectives: Linear algebraic characterizations of identifiability in inverse reinforcement learning L4DC 2024 Making AI Policies Transparent to Humans through Demonstrations AAAI 2024